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  • Piya Pal
  • 2010
A new array geometry, which is capable of significantly increasing the degrees of freedom of linear arrays, is proposed. This structure is obtained by systematically nesting two or more uniform linear arrays and can provide <i>O</i>(<i>N</i><sup>2</sup>) degrees of freedom using only <i>N</i> physical sensors when the second-order statistics of the received(More)
A new approach to super resolution line spectrum estimation in both temporal and spatial domain using a coprime pair of samplers is proposed. Two uniform samplers with sample spacings MT and NT are used where M and N are coprime and T has the dimension of space or time. By considering the difference set of this pair of sample spacings (which arise naturally(More)
This paper considers the sampling of temporal or spatial wide sense stationary (WSS) signals using a co-prime pair of sparse samplers. Several properties and applications of co-prime samplers are developed. First, for uniform spatial sampling with M and N sensors where M and N are co-prime with appropriate interelement spacings, the difference co-array has(More)
A new framework for the problem of sparse support recovery is proposed, which exploits statistical information about the unknown sparse signal in the form of its correlation. A key contribution of this paper is to show that if existing algorithms can recover sparse support of size s, then using such correlation information, the guaranteed size of(More)
— We propose a novel approach to the design of focusing matrices which play important role in the coherent methods for wideband direction-of-arrival estimation. We call this 'autofocusing' because unlike the conventional methods, our technique constructs the focusing matrices entirely by processing the received signal and does not require any preliminary(More)
Coprime sampling and coprime sensor arrays have been introduced recently for the one-dimensional (1-D) case, and applications in beamforming and direction finding discussed. A pair of coprime arrays can be used to sample a wide-sense stationary signal sparsely, and then reconstruct the autocorrelation at a significantly denser set of points. All(More)
A new class of two dimensional arrays with sensors on lattice(s) is proposed, whose difference co-array can give rise to a virtual two dimensional array with much larger number of elements on a &#x201C;dense&#x201D; lattice. This structure is obtained by systematically nesting two arrays, one with sensors on a sparse lattice and the other on a dense lattice(More)
This paper explores the practical application of a new class of two dimensional arrays, namely, the two dimensional nested arrays, in array processing problems like two dimensional direction of arrival estimation. Nested arrays constitute a class of two dimensional arrays with physical sensors on lattice(s), whose difference co-array gives rise to a virtual(More)
A finite duration sequence exhibiting periodicities does not in general admit a sparse representation in terms of the DFT basis unless the period is a divisor of the duration. This paper develops a dictionary called the Farey dictionary for the efficient representation of such sequences. It is shown herein that this representation is especially useful for(More)
Recently, direction-of-arrival estimation (DOA) algorithms based on arbitrary even-order (2<i>q</i>) cumulants of the received data have been proposed, giving rise to new DOA estimation algorithms, namely the 2<i>q</i> MUSIC algorithm. In particular, it has been shown that the 2<i>q</i> MUSIC algorithm can identify <i>O</i>(<i>Nq</i>) statistically(More)